Research on knowledge discovery from incomplete database based on evolutionary computation with accumulation mechanism
| Project/Area Number |
24500191
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Fukuoka Dental College |
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Principal Investigator |
SHIMADA Kaoru 福岡歯科大学, 口腔歯学部, 准教授 (20454100)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2014: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2012: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
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| Keywords | データマイニング / ソフトコンピューティング / 人工知能 / 欠損値 |
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| Outline of Final Research Achievements |
In this research, a method of missing value prediction for incomplete database was proposed based on the evolutionary computation with accumulation mechanism of association rule mining. Its validity was confirmed by experiments using medical data sets and so on. Methods for rule discovery from incomplete databases were proposed and characteristics of rule measurements of the extracted rules were evaluated. In addition, a rule-based continuous value prediction method was proposed adopting an application of artificial missing values, and its effectiveness was confirmed by large real data sets.
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Report
(4 results)
Research Products
(11 results)
